Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques include: obtaining input MR spatial frequency data obtained by imaging the subject using the MRI system; generating an MR image of the subject from the input MR spatial frequency data using a neural network model comprising: a pre-reconstruction neural network configured to process the input MR spatial frequency data; a reconstruction neural network configured to generate at least one initial image of the subject from output of the pre-reconstruction neural network; and a post-reconstruction neural network configured to generate the MR image of the subject from the at least one initial image of the subject.

Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.

Generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system by: generating first and second sets of one or more MR images from first and second input MR data; aligning the first and second sets of MR images using a neural network model comprising first and second neural networks, the aligning comprising: estimating, using the first neural network, a first transformation between the first and second sets of MR images; generating a first updated set of MR images from the second set of MR images using the first transformation; estimating, using the second neural network, a second transformation between the first set and the first updated set of MR images; and aligning the first set of MR images and the second set of MR images at least in part by using the first transformation and the second transformation.

Techniques for generating magnetic resonance (MR) images from MR data obtained by a magnetic resonance imaging (MRI) system comprising a plurality of RF coils configured to detect RF signals. The techniques include: obtaining a plurality of input MR datasets obtained by the MRI system to image a subject, each of the plurality of input MR datasets comprising spatial frequency data and obtained using a respective RF coil in the plurality of RF coils; generating a respective plurality of MR images from the plurality of input MR datasets by using an MR image reconstruction technique; estimating, using a neural network model, a plurality of RF coil profiles corresponding to the plurality of RF coils; generating an MR image of the subject using the plurality of MR images and the plurality of RF coil profiles; and outputting the generated MR image.

The present disclosure relates to systems, methods, and non-transitory computer readable media for generating augmented reality representations of recommended products based on style compatibility with real-world surroundings. For example, the disclosed systems can identify a real-world object within a camera feed and can utilize a 2D-3D alignment algorithm to identify a three-dimensional model that matches the real-world object. In addition, the disclosed systems can utilize a style compatibility algorithm to generate recommended products based on style compatibility in relation to the identified three-dimensional model. The disclosed systems can further utilize a color compatibility algorithm to determine product textures which are color compatible with the real-world surroundings and generate augmented reality representations of recommended products to provide as an overlay of the real-world environment of the camera feed.

Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.

Optical imaging includes: configuring a spatial mode sorter to provide, in response to a received input optical signal, a separate output optical signal for each spatial mode in a set of target spatial modes: receiving a set of output optical signals from the spatial mode sorter during a detection interval of time: processing information based at least in part on the set of output optical signals received in the detection interval of time: and providing an estimated measurement for discriminating among a first set of two or more predetermined target images based at least in part on information derived from the processing. During the detection interval of time, a total number of the output optical signals is greater than two and less than ten.

An optical correlator includes a first spatial light modulator arranged to receive light from a light source and configured to selectively attenuate the light; a first focusing layer arranged to receive the selectively-attenuated light from the first spatial light modulator and configured to focus the selectively-attenuated light; a first spacer layer substantially transparent to the light from the light source, the first focusing layer being disposed on the first spacer layer; a second spatial light modulator arranged in a Fourier optical relationship with respect to the first spatial light modulator and configured to selectively attenuate the focused light from the first focusing layer to provide twice-attenuated light, the second spatial light modulator being disposed on the first spacer layer opposite the first focusing layer; a second spacer layer substantially transparent to the light from the light source, the second spatial light modulator being disposed on the second spacer layer and positioned between the first and second spacer layers; a second focusing layer disposed on the second spacer layer opposite the second spatial light modulator and arranged to receive light from the second spatial light modulator and configured to focus the twice-attenuated light to provide focused, twice-attenuated; and a sensor array arranged to receive light from the second focusing layer and configured to detect spatial intensity variations of the focused, twice-attenuated light.

Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.

The invention relates to methods of contactlessly determining the linear dimensions of an object and can be used for determining the anthropomorphic dimensions of parts of a person's body when virtually selecting and ordering clothes online and during the manufacture of the same. A method of measuring the linear dimensions of an object comprises: capturing a set of images of a measured object from different perspectives, while placing a reference object with known dimensions and of a known shape in the frame such that the dimensions are readable from the image; and processing the images with a computational algorithm. The technical effect consists in increasing the accuracy of contactless determination of the linear dimensions, increasing the speed of obtaining the measurement result by the use of computer vision algorithms and neural network techniques for analyzing the images without human involvement in the process of determining the dimensions of object being measured, and thereby eliminating the occurrence of errors that could be caused by human inattention.